Parallelization of adaptive Bayesian cubature using multimodal optimization algorithms

PurposeBayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been develope...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Engineering computations Jg. 41; H. 2; S. 413 - 437
Hauptverfasser:	Hong, Fangqi, Wei, Pengfei, Beer, Michael
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bradford Emerald Publishing Limited 16.04.2024 Emerald Group Publishing Limited
Schlagworte:	Algorithms Approximation Bayesian analysis Cluster analysis Clustering Design of experiments Engineering Experiments Integrals Maxima Numerical analysis Optimization Optimization algorithms Partial differential equations Probability distribution Stochastic models Vector quantization Adaptive experiment design Parallel computation Acquisition function Multimodal optimization Bayesian cubature
ISSN:	0264-4401, 1758-7077
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!